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Mastering AI Overviews For Greater Search Visibility
The document discusses advanced SEO strategies and the impact of AI on search engine results, emphasizing the importance of visual SERP analytics and the evolution of user behavior in search queries. It highlights the increasing prevalence of AI overviews, the need for proactive content indexing, and the significance of traditional metrics versus AI-derived metrics in understanding click-through rates and search performance. Additionally, it presents insights on optimizing content for both commercial and informational queries, and the necessity for ongoing adjustments in digital strategies to enhance visibility across various search platforms.
In this document
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Introduction of Botify for SEO automation and Data pipeline like DemandSphere for visual analytics.
Discussion on the Modern SERP and limitations of traditional metrics in revealing CTR impacting factors.
Exploration of pixel depth in SERP and its correlation to click-through rates (CTR) and user behavior.
Details of research study on AI impact, total keywords, and the critical need to measure AI overview effects.
Examining SERP data showing different keyword types and the presence of AIOs impacting queries.
Analysis of featured snippets and AI Overviews concerning average pixel heights and organic ranking fundamentals.
Introduction to vector embeddings and cosine similarity for evaluating AI overview links in SERP.
Discussion on limitations of traditional language models (LLMs) in providing current content.
Overview of how GenAI search enhances answers using fresh content from traditional indexes.
Implications of Bing's role in the SEO landscape and the importance of webpage indexability.
Strategies for maintaining clean sitemaps, utilizing real-time indexing, and executing effective campaigns.
Announcement of a whitepaper sharing insights from the AI Overviews study and closing remarks from speakers.
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Mastering AI Overviews For Greater Search Visibility
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- 2. Automation & Deployment Botify:Be Found across all traditional and generative search engines Aggregation & Prioritization BRAND DATA Web Crawler Search intent via GSC Logs Data Revenue Data
- 3. DemandSphere Overview Enterprise-scale, visual SERPanalytics Automated SEO data warehouse & pipeline
- 4.
- 5. Traditional Google SearchConsole metrics
- 6. Traditional metrics donot reveal factors that impact CTR Average Position (Max. Potential Traffic) Impressions (depends on Avg. Pos.) Clicks CTR (clicks / impressions)
- 7. Traditional metrics donot reveal factors that impact CTR Average Position (Max. Potential Traffic) Impressions (depends on Avg. Pos.) Clicks CTR (clicks / impressions) What happened? Derived metrics What happened? Derived metrics
- 8. Traditional metrics donot reveal factors that impact CTR Average Position (Max. Potential Traffic) Impressions (depends on Avg. Pos.) Clicks CTR (clicks / impressions) WHY? What happened? Derived metrics What happened? Derived metrics
- 9. Pixel depth andfold appearance determines attention Attention determines click-through rates (CTR) SERP shape is one of the best predictors of user behavior on the internet Visual SERP analytics enables pre-click predictions 330 pixels 540 pixels Pixel depth: 900 pixels Pixels = Attention
- 10. Anatomy of anAI Overview Google generative overview Key points 394 Average Pixel Height Expanded AIO example Links: Links overview Links (show all) Links are generally pulled from top 12 rankings and have a high cosine similarity to the generated summary
- 11. Research study intoAI Overview impact 120,778 Total Keywords 36,000 Commercial Keywords 85,638 Informational Keywords 22 Websites 10 E-Commerce 10 Brands 2 Publishers
- 12. Framing this study MeasuringAI Overview impact for your own brand is critical
- 13. Framing this study MeasuringAI Overview impact for your own brand is critical Global AI Overview rollout is not complete
- 14. Framing this study MeasuringAI Overview impact for your own brand is critical Global AI Overview rollout is not complete User behaviour is diverse
- 15. running shoes What arethe best running shoes? Leveraging Commercial + PAAs to “force” AIOs Commercial Informational Can you wear running shoes for walking all day? Informational What shoes to run on a trail? Informational Are running shoes machine washable? Informational
- 16. Total SERPs 120,778 Commercial 36,000 Informational 85,638 # ofSites 22 With AIOs 57,263 AIO % 47% Keyword Set Breakdown SERPs with AIOs AIO Intent Breakdown AI Overviews appeared for 47% of the keywords
- 17. 19% of Commercialtriggered AIO 59% of Informational triggered AIO Commercial vs. Informational Breakdowns
- 18. 55% of queriesunder 1,000 monthly searches trigger AIOs
- 19. Featured Snippets appear regularly,even when AI Overviews are present. This is important to track because of the net pixel impact for the searcher. Featured Snippets aren’t going away, they appeared for 60.5% of queries
- 20. Featured Snippet Avg. PixelHeight 237.75 AIO Avg. Pixel Height 394.44 Combined Pixel Height 632.19 Avg. Screen Resolution Height (US) 942.29 AIO and FS pixels take up 67% of Avg. Screen Height 394.44 pixels 237.75 pixels https://gs.statcounter.com/screen-resolution-stats/desktop/north-america
- 21. Defining head, mid,and long tail for this study Head 1-2 words Mid 3-4 words Long Tail 5+ words
- 22. Head Keywords 8.9% Mid Keywords 17.6% TailKeywords 73.6% Commercial Informational AI Overviews are appearing more in tail queries
- 23. The fundamentals stillmatter Performing well in organic rankings is the strongest influencing factor for appearance in AI Overview links AI Overview links can be thought of as the new SERP – when they appear 75% of AI Overview links came from position 12 or higher 4 Median Organic Rank 12.03 Average Organic Rank 12 75th Percentile
- 24. Generally appear inpositions 1-12 in organic rankings Presence is currently correlated with medium to high Cosine Similarity score All best practices apply with regard to organic rankings Cosine Similarity allows us to mathematically compare the similarity between two bodies of text. How sources are selected for inclusion in AI Overviews
- 25. Vector Embeddings 0.001 .0044.012 …. 0.001 .0043 .011 …. 0.001 .0041 .009 …. Embedding model “marathon training” “running shoes” “route tracker app” Cluster visualization with projections
- 26. Evaluating AI Overviewlinks with Cosine Similarity 0.82 0.78 0.73 Cosine Similarity
- 27. Relationship of CosineSimilarity to top results
- 29. On their own,LLMs are not up to date
- 30. User asks aquestion Limited answer due to lack of recent content to source it from LLM use static content to answer the question GenAI search relies on LLMs, models that are pre-trained on “static” content
- 31. GenAI search pullsfresh content from traditional indexes using Retrieval-Augmented Generation (RAG) User asks a question Augmented answer LLM use trained model with relevant fresh content Fresh content retrieval (RAG) Query Relevant fresh content How GenAI search engines work today + Google scrapping + New indexes
- 32. Today, Bing isat the center of the non-Google Universe …Tomorrow, ?
- 33. Other Players areAggressively Crawling Your Site ChatGPT-User crawl volume over major retailers in the US Why are they crawling ● LLM training ● Real-time retrieval ● Indexation Source: Botify
- 34. Ensure your pagesare indexable Bring your most strategic pages at the top of your hierarchy Use automation and pre-rendering solution to deliver lightening fast pages to search engine Timeless Tactics - Crawl Budget
- 35. Keep ‘em Clean Includeall (and only) your strategic pages Update them regularly, automate Don’t forget about your organic shopping feed Timeless Tactics - Sitemaps
- 36. IndexNow: Take control ofyour SEO game with real-time indexing Don’t wait for crawlers! Elevate your website’s performance and visibility with immediate content updates in multiple search engines.
- 37. Push To Bing: Guidesearch & AI bots to index your pages Submit your content directly to Bing’s index Guarantee visibility across Bing and all AI engines powered by Bing’s index
- 38. Intelligence has alifecycle that requires action Review and plan Allow for some time after the campaign to ensure that data is vetted. Review successes and failures, establish regression baselines, and plan next phase. Execute campaign Create new content, optimize existing content, work on digital PR, etc. This execution phase should be tied to achieving strategic and operational goals Define monitoring Hone research data set into campaign and group-focused segments, which can be prioritized for action Define strategic goals Intelligence lifecycles are derived from strategic vision and initiatives Research opportunities Initial SERP and search volume focused analysis of competitive and market landscape 01 05 04 03 02
- 39. AI Overviews Study: InsideGoogle's New Search Reality Find all the insights and actionable items and more in our upcoming joined whitepaper. Coming up next week
- 40. Ray Grieselhuber Founder &CEO DemandSphere linkedin.com/in/raygrieselhuber Thank you Global VP of Professional Services Botify linkedin.com/in/timresnik Tim Resnik Book a demo with Botify Book a demo with DemandSphere